This first video from Xiph.Org presents the technical foundations of modern digital media via a half-hour firehose of information. One community member called it "a Uni lecture I never got but really wanted."

This first video from Xiph.Org presents the technical foundations of modern digital media via a half-hour firehose of information. One community member called it "a Uni lecture I never got but really wanted."

The program offers a brief history of digital media, a quick summary of the sampling theorem, and myriad details of low level audio and video characterization and formatting. It's intended for budding geeks looking to get into video coding, as well as the technically curious who want to know more about the media they wrangle for work or play.

The program offers a brief history of digital media, a quick summary of the sampling theorem, and myriad details of low level audio and video characterization and formatting. It's intended for budding geeks looking to get into video coding, as well as the technically curious who want to know more about the media they wrangle for work or play.

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<br/><br/><br/>

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<br/>

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<br/>

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See also: [[Videos/Digital_Show_and_Tell|Episode 02: Digital Show and Tell]]

*[http://www.xiph.org/about/ About Xiph.Org]: Why you should care about open media

*[http://www.0xdeadbeef.com/weblog/2010/01/html5-video-and-h-264-what-history-tells-us-and-why-were-standing-with-the-web/ HTML5 Video and H.264: what history tells us and why we're standing with the web]: Chris Blizzard of Mozilla on free formats and the open web

*[http://www.0xdeadbeef.com/weblog/2010/01/html5-video-and-h-264-what-history-tells-us-and-why-were-standing-with-the-web/ HTML5 Video and H.264: what history tells us and why we're standing with the web]: Chris Blizzard of Mozilla on free formats and the open web

*Wikipedia: [[WikiPedia:Passive_analogue_filter_development|The history of analog filters]] such as the [[WikiPedia:RC circuit|RC low-pass]] shown connected to the [[wikipedia:Spectrum_analyzer|spectrum analyzer]] in the video.

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<br style="clear:both;"/>

<br style="clear:both;"/>

===sample rate===

===sample rate===

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<small>[[Talk:A_Digital_Media_Primer_For_Geeks_(episode_1)#Raw_.28digital_audio.29_meat|Discuss this section]]</small>

[[Image:Dmpfg_009.jpg|360px|right]]

[[Image:Dmpfg_009.jpg|360px|right]]

[[Image:Dmpfg_008.jpg|360px|right]]

[[Image:Dmpfg_008.jpg|360px|right]]

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process. First, that a digital signal can't represent any

process. First, that a digital signal can't represent any

frequencies above the Nyquist frequency. Second, and this is the new

frequencies above the Nyquist frequency. Second, and this is the new

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part, if we don't remove those frequencies with a low-pass filter

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part, if we don't remove those frequencies with a low-pass [[wikipedia:Audio_filter|filter]]

* [[wikipedia:Roll-off|Wikipedia's article on filter roll-off]], to learn why it's hard to build analog filters with a very narrow [[wikipedia:Transition_band|transition band]] between the [[wikipedia:Passband|passband]] and the [[wikipedia:Stopband|stopband]].

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* [[wikipedia:Roll-off|Wikipedia's article on filter roll-off]], to learn why it's hard to build analog filters with a very narrow [[wikipedia:Transition_band|transition band]] between the [[wikipedia:Passband|passband]] and the [[wikipedia:Stopband|stopband]]. Filters that achieve such hard edges often do so at the expense of increased [[wikipedia:Ripple_(filters)#Frequency-domain_ripple|ripple]] and [http://www.ocf.berkeley.edu/~ashon/audio/phase/phaseaud2.htm phase distortion].

* [http://wiki.multimedia.cx/index.php?title=PCM Some more minutiae] about PCM in practice.

* [http://wiki.multimedia.cx/index.php?title=PCM Some more minutiae] about PCM in practice.

* [http://wiki.multimedia.cx/index.php?title=YUV4MPEG2 The y4m format] is the most common simple container for raw YUV video. People occasionally use [[OggYUV]] to store it in Ogg instead.

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* YCbCr is defined in terms of RGB by the ITU in two incompatible standards: [[wikipedia:Rec. 601|Rec. 601]] and [[wikipedia:Rec. 709|Rec. 709]]. Both conversion standards are lossy, which has prompted some to adopt a lossless alternative called [http://wiki.multimedia.cx/index.php?title=YCoCg YCoCg].

* Learn about [[wikipedia:High_dynamic_range_imaging|high dynamic range imaging]], which achieves better representation of the full range of brightnesses in the real world by using more than 8 bits per channel.

* Learn about [[wikipedia:High_dynamic_range_imaging|high dynamic range imaging]], which achieves better representation of the full range of brightnesses in the real world by using more than 8 bits per channel.

* Learn about how [[wikipedia:Trichromatic_vision|trichromatic color vision]] works in humans, and how human color perception is encoded in the [[wikipedia:CIE 1931 color space|CIE 1931 XYZ color space]].

* Learn about how [[wikipedia:Trichromatic_vision|trichromatic color vision]] works in humans, and how human color perception is encoded in the [[wikipedia:CIE 1931 color space|CIE 1931 XYZ color space]].

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** If we were all [[wikipedia:Dichromacy|dichromats]] then video would only need two color channels. Some humans might be [[wikipedia:Tetrachromacy#Possibility_of_human_tetrachromats|tetrachromats]], in which case they would need an additional color channel for video to fully represent their vision.

** If we were all [[wikipedia:Dichromacy|dichromats]] then video would only need two color channels. Some humans might be [[wikipedia:Tetrachromacy#Possibility_of_human_tetrachromats|tetrachromats]], in which case they would need an additional color channel for video to fully represent their vision.

* YCbCr is defined in terms of RGB by the ITU in two incompatible standards: [[wikipedia:Rec. 601|Rec. 601]] and [[wikipedia:Rec. 709|Rec. 709]]. Both conversion standards are lossy, which has prompted some to adopt a lossless alternative called [http://wiki.multimedia.cx/index.php?title=YCoCg YCoCg].

* There are several common general-purpose container formats: [[wikipedia:Audio_Video_Interleave|AVI]], [[wikipedia:Matroska|Matroska]], [[wikipedia:Ogg|Ogg]], [[wikipedia:QuickTime_File_Format|QuickTime]], and [[wikipedia:Comparison_of_container_formats|many others]]. These can contain and interleave many different types of media streams.

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* Some special-purpose containers have been designed that can only hold one format:

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** [http://wiki.multimedia.cx/index.php?title=YUV4MPEG2 The y4m format] is the most common single-purpose container for raw YUV video. It can also be stored in a general-purpose container, for example in Ogg using [[OggYUV]].

** [[wikipedia:WAV|WAV]] and [[wikipedia:AIFC|AIFC]] are semi-single-purpose formats. They're audio-only, and typically contain raw PCM audio, but are occasionally used to store other kinds of audio data ... even MP3!

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<br style="clear:both;"/>

==Credits==

==Credits==

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[[Image:Dmpfg_018.jpg|360px|right]]

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[[Image:Dmpfg_019.png|360px|right]]

In the past thirty minutes, we've covered digital audio, video, some

In the past thirty minutes, we've covered digital audio, video, some

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Intro, title and credits music:<br>

Intro, title and credits music:<br>

"Boo Boo Coming", by Joel Forrester<br>

"Boo Boo Coming", by Joel Forrester<br>

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Performed by the Microscopic Septet<br>

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Performed by the [http://microscopicseptet.com/ Microscopic Septet]<br>

Used by permission of Cuneiform Records.<br>

Used by permission of Cuneiform Records.<br>

Original source track All Rights Reserved.<br>

Original source track All Rights Reserved.<br>

[http://www.cuneiformrecords.com www.cuneiformrecords.com]

[http://www.cuneiformrecords.com www.cuneiformrecords.com]

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This Video Was Produced Entirely With Free and Open Source Software

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This Video Was Produced Entirely With Free and Open Source Software:<br>

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GNU

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Linux

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Fedora

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Cinelerra

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The Gimp

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Audacity

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Postfish

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Gstreamer

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CC BY-NC-SA

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A Co-Production of Xiph.Org and Red Hat Inc.

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(C) 2010, Some Rights Reserved

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<br style="clear:both;"/>

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==The making of…==

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<small>[[Talk:A_Digital_Media_Primer_For_Geeks_(episode_1)#The_making_of.E2.80.A6|Discuss this section]]</small>

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===Equipment===

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====Camera====

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Canon HV40 HDV camera w/ wide-angle lens operating on a tripod.

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The wide angle lens gives the camera a nice close macro mode, and approximately triples the amount of light coming into the sensor for a given zoom/aperture. Useful for shooting indoors at night.

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No additional lighting kit was used.

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====Audio====

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Two Crown PCC160 boundary microphones placed on a table approximately 4-8 feet in front of the speaker, run through a cheap Behringer portable mixer and into the camera's microphone input.

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No additional audio kit was used.

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====Sundries====

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Whiteboard markers by 'Bic'

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Drawing aids by Staedtler, McMaster Carr, and 'Generic'.

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===Video shooting sequence===

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Scenes were pre-scripted and memorized, usually with lots of on-the-fly revision. (In the future... I'm totally getting a teleprompter. Wh000. OTOH, I can totally rattle off the entire video script from beginning to end as a party trick, thus ensuring I'll not be invited to many parties --Monty).

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Diagrams were drawn by hand on a physical whiteboard with whiteboard markers and magnetic T-squares, triangles, and yardsticks. Despite looking a lot like greenscreen work, there is no image compositing in use (actually-- there are two small composites where an error in a whiteboard diagram was corrected by subtracting part of the original image and then adding a corrected version of the diagram).

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Camera operated in 24F shutter priority mode (Tv set to "24") with exposure and white balance both calibrated to the white board (or a white piece of paper) and locked. Microphone attenuation setting active, with gain locked such that room noise peaked at -40dB (all the rooms in the shooting sequences were noisy due to the building's ventilation system, or active equipment). Lighting in the whiteboard rooms tended to be odd, with little relative light cast on a presenter standing just in front of the whiteboard; a presenter is practically standing in the room's only shadow. Most of the room light is focused on the table and walls. Additional fill lighting kit would have been useful, but for the first vid, I didn't want 'perfect' to be the enemy of 'good'.

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Autofocus used for whiteboard scenes, manual focus used for several workshop scenes as the autofocus tended to hunt continuously in very low light.

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Continuous capture to a Thinkpad with firewire input via a simple gstreamer script.

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===Production sequence===

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====All hail Cinelerra. You better hail, or Cinelerra will get pissy about it.====

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Most of the production sequence hinged on making Cinelerra happy; it is a hulking rusty cast iron WWI tank of a program that can seem like it's composed entirely of compressed bugs. That said, it was neither particularly crashy nor did it ever accidentally corrupt or lose work. It was also the only FOSS editor with a working 2D compositor. It got the job done once I found a workflow it would cope with (and fixed a number of bugs; these fixes are available from my cinelerra Git repo at http://git.xiph.org/?p=users/xiphmont/cinelerraCV.git;a=summary)

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====Choosing takes====

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Each shooting session yielded four to six hours of raw video. The first step was to load the raw video into the cinelerra timeline, label each complete take, compare and choose the take to use, then render the chosen take out to a raw clip as a YUV4MPEG raw video file and a WAV raw audio file. Be careful that Settings->Align Cursor On Frames is set, else the audio and video renders won't start on the same boundary.

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====Postprocessing====

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At this point, the raw video clips were adjusted for gamma, contrast, and saturation in gstreamer and mplayer. In the earlier shoots the camera was underexposing due to pilot error, which required quite a bit of gamma and saturation inflation to 'correct' (there is no real correction as the low-end data is gone, but it's possible to make it look better). Later shoots used saner settings and the adjustments were mostly to keep different shooting sessions more uniform. The whiteboard tends not to look white because it's mildly reflective, and picked up the color of the cyan and orange audio baffles in the room like a big diffuse mirror.

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The audio was both noisy (due to the building's ventilation system which either sounded like a low loud rumble or a jet-engine taking off) and reverberant (the rooms were glass on two sides and plaster on the other two). Early takes used no additional sound absorbing material in the rooms, and the Postfish filtering and deverb was used heavily. It gives the early audio in the vid a slightly odd, processed feel (I had almost decided the original audio was simply unusable). Later takes used some big fleece 'soft flats' in the room to absorb some additional reverb, and the later takes are less heavily filtered.

Audio special effects were one-offs, mostly done using Sox. The processed demo sections of audio were then spliced back into the original audio takes using Audactity.

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Video special effects (eg, removing a color channel, etc) were done by writing quick, one-off filters in C for y4oi. A few effects were done by dumping a take as a directory full of PNGs and then batch-processing the PNGs again using a one-off C program, then reassembling with mplayer. Video effects were then stitched back into the original video takes in Cinelerra.

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====Editing====

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All editing was done in Cinelerra. This primarily consisted of stitching the individual takes back together with crossfades. All input and rendering output were done with raw YUV4MPEG and WAV files. Note that making this work well and correctly required several patches to the YUV4MPEG handler and colorspace conversion code.

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[http://www.gnu.org/ GNU]<br>

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[http://www.linux.org/ Linux]<br>

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[http://fedoraproject.org/ Fedora]<br>

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[http://cinelerra.org/ Cinelerra]<br>

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[http://www.gimp.org/ The Gimp]<br>

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[http://audacity.sourceforge.net/ Audacity]<br>

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[http://svn.xiph.org/trunk/postfish/README Postfish]<br>

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[http://gstreamer.freedesktop.org/ Gstreamer]<br>

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====Encoding====

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All trademarks are the property of their respective owners.

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Encoding was done by hand external to Cinelerra using mplayer for final postprocessing, the example_encoder included with the [Ptalarbvorm] Theora source distribution, and ivfenc for WebM.

<center><font size="+1">''[[/making|Learn more about the making of this video…]]''</font></center>

Revision as of 04:09, 26 February 2013

Wiki edition

This first video from Xiph.Org presents the technical foundations of modern digital media via a half-hour firehose of information. One community member called it "a Uni lecture I never got but really wanted."

The program offers a brief history of digital media, a quick summary of the sampling theorem, and myriad details of low level audio and video characterization and formatting. It's intended for budding geeks looking to get into video coding, as well as the technically curious who want to know more about the media they wrangle for work or play.

Introduction

Workstations and high-end personal computers have been able to
manipulate digital audio pretty easily for about fifteen years now.
It's only been about five years that a decent workstation's been able
to handle raw video without a lot of expensive special purpose
hardware.

But today even most cheap home PCs have the processor power and
storage necessary to really toss raw video around, at least without
too much of a struggle. So now that everyone has all of this cheap media-capable hardware,
more people, not surprisingly, want to do interesting
things with digital media, especially streaming. YouTube was the first huge
success, and now everybody wants in.

Well good! Because this stuff is a lot of fun!

It's no problem finding consumers for digital media. But here I'd
like to address the engineers, the mathematicians, the hackers, the
people who are interested in discovering and making things and
building the technology itself. The people after my own heart.

Digital media, compression especially, is perceived to be super-elite,
somehow incredibly more difficult than anything else in computer
science. The big industry players in the field don't mind this
perception at all; it helps justify the staggering number of very
basic patents they hold. They like the image that their media
researchers "are the best of the best, so much smarter than anyone
else that their brilliant ideas can't even be understood by mere
mortals." This is bunk.

Digital audio and video and streaming and compression offer endless
deep and stimulating mental challenges, just like any other
discipline. It seems elite because so few people have been
involved. So few people have been involved perhaps because so few
people could afford the expensive, special-purpose equipment it
required. But today, just about anyone watching this video has a
cheap, general-purpose computer powerful enough to play with the big
boys. There are battles going on today around HTML5 and browsers and
video and open vs. closed. So now is a pretty good time to get
involved. The easiest place to start is probably understanding the
technology we have right now.

This is an introduction. Since it's an introduction, it glosses over a
ton of details so that the big picture's a little easier to see.
Quite a few people watching are going to be way past anything that I'm
talking about, at least for now. On the other hand, I'm probably
going to go too fast for folks who really are brand new to all of
this, so if this is all new, relax. The important thing is to pick out
any ideas that really grab your imagination. Especially pay attention
to the terminology surrounding those ideas, because with those, and
Google, and Wikipedia, you can dig as deep as interests you.

Analog vs Digital

Sound is the propagation of pressure waves through air, spreading out
from a source like ripples spread from a stone tossed into a pond. A
microphone, or the human ear for that matter, transforms these passing
ripples of pressure into an electric signal. Right, this is
middle school science class, everyone remembers this. Moving on.

That audio signal is a one-dimensional function, a single value
varying over time. If we slow the 'scope down a bit... that should be
a little easier to see. A few other aspects of the signal are
important. It's continuous in both value and time; that is, at any
given time it can have any real value, and there's a smoothly varying
value at every point in time. No matter how much we zoom in, there
are no discontinuities, no singularities, no instantaneous steps or
points where the signal ceases to exist. It's defined
everywhere. Classic continuous math works very well on these signals.

A digital signal on the other hand is discrete in both value and time.
In the simplest and most common system, called Pulse Code Modulation,
one of a fixed number of possible values directly represents the
instantaneous signal amplitude at points in time spaced a fixed
distance apart. The end result is a stream of digits.

Now this looks an awful lot like this. It seems intuitive that we
should somehow be able to rigorously transform one into the other, and
good news, the Sampling Theorem says we can and tells us
how. Published in its most recognizable form by Claude Shannon in 1949
and built on the work of Nyquist, and Hartley, and tons of others, the
sampling theorem states that not only can we go back and
forth between analog and digital, but also lays
down a set of conditions for which conversion is lossless and the two
representations become equivalent and interchangeable. When the
lossless conditions aren't met, the sampling theorem tells us how and
how much information is lost or corrupted.

Up until very recently, analog technology was the basis for
practically everything done with audio, and that's not because most
audio comes from an originally analog source. You may also think that
since computers are fairly recent, analog signal technology must have
come first. Nope. Digital is actually older. The telegraph predates
the telephone by half a century and was already fully mechanically
automated by the 1860s, sending coded, multiplexed digital signals
long distances. You know... tickertape. Harry Nyquist of Bell Labs was
researching telegraph pulse transmission when he published his
description of what later became known as the Nyquist frequency, the
core concept of the sampling theorem. Now, it's true the telegraph
was transmitting symbolic information, text, not a digitized analog
signal, but with the advent of the telephone and radio, analog and
digital signal technology progressed rapidly and side-by-side.

Audio had always been manipulated as an analog signal because... well,
gee, it's so much easier. A second-order low-pass filter, for example,
requires two passive components. An all-analog short-time Fourier
transform, a few hundred. Well, maybe a thousand if you want to build
something really fancy (bang on the 3585). Processing signals
digitally requires millions to billions of transistors running at
microwave frequencies, support hardware at very least to digitize and
reconstruct the analog signals, a complete software ecosystem for
programming and controlling that billion-transistor juggernaut,
digital storage just in case you want to keep any of those bits for
later...

So we come to the conclusion that analog is the only practical way to
do much with audio... well, unless you happen to have a billion
transistors and all the other things just lying around. And since we
do, digital signal processing becomes very attractive.

For one thing, analog componentry just doesn't have the flexibility of
a general purpose computer. Adding a new function to this
beast [the 3585]... yeah, it's probably not going to happen. On a digital
processor though, just write a new program. Software isn't trivial,
but it is a lot easier.

Perhaps more importantly though every analog component is an
approximation. There's no such thing as a perfect transistor, or a
perfect inductor, or a perfect capacitor. In analog, every component
adds noise and distortion, usually not very much, but it adds up. Just
transmitting an analog signal, especially over long distances,
progressively, measurably, irretrievably corrupts it. Besides, all of
those single-purpose analog components take up a lot of space. Two
lines of code on the billion transistors back here can implement a
filter that would require an inductor the size of a refrigerator.

Digital systems don't have these drawbacks. Digital signals can be
stored, copied, manipulated, and transmitted without adding any noise
or distortion. We do use lossy algorithms from time to time, but the
only unavoidably non-ideal steps are digitization and reconstruction,
where digital has to interface with all of that messy analog. Messy
or not, modern conversion stages are very, very good. By the
standards of our ears, we can consider them practically lossless as
well.

With a little extra hardware, then, most of which is now small and
inexpensive due to our modern industrial infrastructure, digital audio
is the clear winner over analog. So let us then go about storing it,
copying it, manipulating it, and transmitting it.

Raw (digital audio) meat

Pulse Code Modulation is the most common representation for
raw audio. Other practical representations do exist: for example, the
Sigma-Delta coding used by the SACD, which is a form of Pulse Density
Modulation. That said, Pulse Code Modulation is far
and away dominant, mainly because it's so mathematically
convenient. An audio engineer can spend an entire career without
running into anything else.

PCM encoding can be characterized in three parameters, making it easy
to account for every possible PCM variant with mercifully little
hassle.

sample rate

The first parameter is the sampling rate. The highest frequency an
encoding can represent is called the Nyquist Frequency. The Nyquist
frequency of PCM happens to be exactly half the sampling rate.
Therefore, the sampling rate directly determines the highest possible
frequency in the digitized signal.

Analog telephone systems traditionally band-limited voice channels to
just under 4kHz, so digital telephony and most classic voice
applications use an 8kHz sampling rate: the minimum sampling rate
necessary to capture the entire bandwidth of a 4kHz channel. This is
what an 8kHz sampling rate sounds like—a bit muffled but perfectly
intelligible for voice. This is the lowest sampling rate that's ever
been used widely in practice.

From there, as power, and memory, and storage increased, consumer
computer hardware went to offering 11, and then 16, and then 22, and
then 32kHz sampling. With each increase in the sampling rate and the
Nyquist frequency, it's obvious that the high end becomes a little
clearer and the sound more natural.

The Compact Disc uses a 44.1kHz sampling rate, which is again slightly
better than 32kHz, but the gains are becoming less distinct. 44.1kHz
is a bit of an oddball choice, especially given that it hadn't been
used for anything prior to the compact disc, but the huge success of
the CD has made it a common rate.

The most common hi-fidelity sampling rate aside from the CD is 48kHz.
There's virtually no audible difference between the two. This video,
or at least the original version of it, was shot and produced with
48kHz audio, which happens to be the original standard for
high-fidelity audio with video.

Super-hi-fidelity sampling rates of 88, and 96, and 192kHz have also
appeared. The reason for the sampling rates beyond 48kHz isn't to
extend the audible high frequencies further. It's for a different
reason.

Stepping back for just a second, the French mathematician Jean
Baptiste Joseph Fourier showed that we can also think of signals like
audio as a set of component frequencies. This frequency-domain
representation is equivalent to the time representation; the signal is
exactly the same, we're just looking at it a different way. Here we see the
frequency-domain representation of a hypothetical analog signal we
intend to digitally sample.

The sampling theorem tells us two essential things about the sampling
process. First, that a digital signal can't represent any
frequencies above the Nyquist frequency. Second, and this is the new
part, if we don't remove those frequencies with a low-pass filter
before sampling, the sampling process will fold them down into the
representable frequency range as aliasing distortion.

Aliasing, in a nutshell, sounds freakin' awful, so it's essential to
remove any beyond-Nyquist frequencies before sampling and after
reconstruction.

Human frequency perception is considered to extend to about 20kHz. In
44.1 or 48kHz sampling, the low pass before the sampling stage has to
be extremely sharp to avoid cutting any audible frequencies below
20kHz but still not allow frequencies above the Nyquist to leak
forward into the sampling process. This is a difficult filter to
build, and no practical filter succeeds completely. If the sampling
rate is 96kHz or 192kHz on the other hand, the low pass has an extra
octave or two for its transition band. This is a much easier filter to
build. Sampling rates beyond 48kHz are actually one of those messy
analog stage compromises.

Most modern PCM uses 16- or 24-bit two's-complement signed integers to
encode the range from negative infinity to zero decibels in 16 or 24
bits of precision. The maximum absolute value corresponds to zero decibels.
As with all the sample formats so far, signals beyond zero decibels, and thus
beyond the maximum representable range, are clipped.

In mixing and mastering, it's not unusual to use floating-point
numbers for PCM instead of integers. A 32 bit IEEE754 float, that's
the normal kind of floating point you see on current computers, has 24
bits of resolution, but a seven bit floating-point exponent increases
the representable range. Floating point usually represents zero
decibels as +/-1.0, and because floats can obviously represent
considerably beyond that, temporarily exceeding zero decibels during
the mixing process doesn't cause clipping. Floating-point PCM takes
up more space, so it tends to be used only as an intermediate
production format.

Lastly, most general purpose computers still read and
write data in octet bytes, so it's important to remember that samples
bigger than eight bits can be in big- or little-endian order, and both
endiannesses are common. For example, Microsoft WAV files are little-endian,
and Apple AIFC files tend to be big-endian. Be aware of it.

channels

The third PCM parameter is the number of channels. The convention in
raw PCM is to encode multiple channels by interleaving the samples of
each channel together into a single stream. Straightforward and extensible.

done!

And that's it! That describes every PCM representation ever. Done.
Digital audio is so easy! There's more to do of course, but at this
point we've got a nice useful chunk of audio data, so let's get some
video too.

Video vegetables (they're good for you!)

One could think of video as being like audio but with two additional
spatial dimensions, X and Y, in addition to the dimension of time.
This is mathematically sound. The Sampling Theorem applies to all
three video dimensions just as it does the single time dimension of
audio.

Audio and video are obviously quite different in practice. For one,
compared to audio, video is huge. Raw CD audio is about 1.4 megabits
per second. Raw 1080i HD video is over 700 megabits per second. That's
more than 500 times more data to capture, process, and store per
second. By Moore's law... that's... let's see... roughly eight
doublings times two years, so yeah, computers requiring about an extra
fifteen years to handle raw video after getting raw audio down pat was
about right.

Basic raw video is also just more complex than basic raw audio. The
sheer volume of data currently necessitates a representation more
efficient than the linear PCM used for audio. In addition, electronic
video comes almost entirely from broadcast television alone, and the
standards committees that govern broadcast video have always been very
concerned with backward compatibility. Up until just last year in the
US, a sixty-year-old black and white television could still show a
normal analog television broadcast. That's actually a really neat
trick.

The downside to backward compatibility is that once a detail makes it
into a standard, you can't ever really throw it out again. Electronic
video has never started over from scratch the way audio has multiple
times. Sixty years worth of clever but obsolete hacks necessitated by
the passing technology of a given era have built up into quite a pile,
and because digital standards also come from broadcast television, all
these eldritch hacks have been brought forward into the digital
standards as well.

In short, there are a whole lot more details involved in digital video
than there were with audio. There's no hope of covering them
all completely here, so we'll cover the broad fundamentals.

resolution and aspect

The most obvious raw video parameters are the width and height of the
picture in pixels. As simple as that may sound, the pixel dimensions
alone don't actually specify the absolute width and height of the
picture, as most broadcast-derived video doesn't use square pixels.
The number of scanlines in a broadcast image was fixed, but the
effective number of horizontal pixels was a function of channel
bandwidth. Effective horizontal resolution could result in pixels that
were either narrower or wider than the spacing between scanlines.

Standards have generally specified that digitally sampled video should
reflect the real resolution of the original analog source, so a large
amount of digital video also uses non-square pixels. For example, a
normal 4:3 aspect NTSC DVD is typically encoded with a display
resolution of 704 by 480, a ratio wider than 4:3. In this case, the
pixels themselves are assigned an aspect ratio of 10:11, making them
taller than they are wide and narrowing the image horizontally to the
correct aspect. Such an image has to be resampled to show properly on
a digital display with square pixels.

frame rate and interlacing

The second obvious video parameter is the frame rate, the number of
full frames per second. Several standard frame rates are in active
use. Digital video, in one form or another, can use all of them. Or,
any other frame rate. Or even variable rates where the frame rate
changes adaptively over the course of the video. The higher the frame
rate, the smoother the motion and that brings us, unfortunately, to
interlacing.

In the very earliest days of broadcast video, engineers sought the
fastest practical frame rate to smooth motion and to minimize flicker
on phosphor-based CRTs. They were also under pressure to use the
least possible bandwidth for the highest resolution and fastest frame
rate. Their solution was to interlace the video where the even lines
are sent in one pass and the odd lines in the next. Each pass is
called a field and two fields sort of produce one complete frame.
"Sort of", because the even and odd fields aren't actually from the
same source frame. In a 60 field per second picture, the source frame
rate is actually 60 full frames per second, and half of each frame,
every other line, is simply discarded. This is why we can't
deinterlace a video simply by combining two fields into one frame;
they're not actually from one frame to begin with.

gamma

The cathode ray tube was the only available display technology for
most of the history of electronic video. A CRT's output brightness is
nonlinear, approximately equal to the input controlling voltage raised
to the 2.5th power. This exponent, 2.5, is designated gamma, and so
it's often referred to as the gamma of a display. Cameras, though,
are linear, and if you feed a CRT a linear input signal, it looks a
bit like this.

As there were originally to be very few cameras, which were
fantastically expensive anyway, and hopefully many, many television
sets which best be as inexpensive as possible, engineers decided to
add the necessary gamma correction circuitry to the cameras rather
than the sets. Video transmitted over the airwaves would thus have a
nonlinear intensity using the inverse of the set's gamma exponent, so that
once a camera's signal was finally displayed on the CRT, the overall
response of the system from camera to set was back to linear again.

Almost.

There were also two other tweaks. A television camera actually uses a
gamma exponent that's the inverse of 2.2, not 2.5. That's just a
correction for viewing in a dim environment. Also, the exponential
curve transitions to a linear ramp near black. That's just an old
hack for suppressing sensor noise in the camera.

Gamma correction also had a lucky benefit. It just so happens that the
human eye has a perceptual gamma of about 3. This is relatively close
to the CRT's gamma of 2.5. An image using gamma correction devotes
more resolution to lower intensities, where the eye happens to have
its finest intensity discrimination, and therefore uses the available
scale resolution more efficiently. Although CRTs are currently
vanishing, a standard sRGB computer display still uses a nonlinear
intensity curve similar to television, with a linear ramp near black,
followed by an exponential curve with a gamma exponent of 2.4. This
encodes a sixteen bit linear range down into eight bits.

color and colorspace

The human eye has three apparent color channels, red, green, and blue,
and most displays use these three colors as additive primaries to
produce a full range of color output. The primary pigments in
printing are Cyan, Magenta, and Yellow for the same reason; pigments
are subtractive, and each of these pigments subtracts one pure color
from reflected light. Cyan subtracts red, magenta subtracts green, and
yellow subtracts blue.

Video can be, and sometimes is, represented with red, green, and blue
color channels, but RGB video is atypical. The human eye is far more
sensitive to luminosity than it is the color, and RGB tends to spread
the energy of an image across all three color channels. That is, the
red plane looks like a red version of the original picture, the green
plane looks like a green version of the original picture, and the blue
plane looks like a blue version of the original picture. Black and
white times three. Not efficient.

For those reasons and because, oh hey, television just happened to
start out as black and white anyway, video usually is represented as a
high resolution luma channel—the black & white—along with
additional, often lower resolution chroma channels, the color. The
luma channel, Y, is produced by weighting and then adding the separate
red, green and blue signals. The chroma channels U and V are then
produced by subtracting the luma signal from blue and the luma signal
from red.

When YUV is scaled, offset, and quantized for digital video, it's
usually more correctly called Y'CbCr, but the more generic term YUV is
widely used to describe all the analog and digital variants of this
color model.

chroma subsampling

The U and V chroma channels can have the same resolution as the Y
channel, but because the human eye has far less spatial color
resolution than spatial luminosity resolution, chroma resolution is
usually halved or even quartered in the horizontal direction, the
vertical direction, or both, usually without any significant impact on the
apparent raw image quality. Practically every possible subsampling
variant has been used at one time or another, but the common choices
today are 4:4:4 video, which isn't actually subsampled at all, 4:2:2 video in
which the horizontal resolution of the U and V channels is halved, and
most common of all, 4:2:0 video in which both the horizontal and vertical
resolutions of the chroma channels are halved, resulting in U and V
planes that are each one quarter the size of Y.

The terms 4:2:2, 4:2:0, 4:1:1, and so on and so forth, aren't complete
descriptions of a chroma subsampling. There's multiple possible ways
to position the chroma pixels relative to luma, and again, several
variants are in active use for each subsampling. For example, motion
JPEG, MPEG-1 video, MPEG-2 video, DV, Theora, and WebM all use or can
use 4:2:0 subsampling, but they site the chroma pixels three different ways.

Motion JPEG, MPEG-1 video, Theora and WebM all site chroma pixels
between luma pixels both horizontally and vertically.

And finally PAL-DV, which is always interlaced, places the chroma
pixels in the same position as every other luma pixel in the
horizontal direction, and vertically alternates chroma channel on
each line.

That's just 4:2:0 video. I'll leave the other subsamplings as homework for the
viewer. Got the basic idea, moving on.

pixel formats

In audio, we always represent multiple channels in a PCM stream by
interleaving the samples from each channel in order. Video uses both
packed formats that interleave the color channels, as well as planar
formats that keep the pixels from each channel together in separate
planes stacked in order in the frame. There are at least 50 different formats in
these two broad categories with possibly ten or fifteen in common use.

Each chroma subsampling and different bit-depth requires a different
packing arrangement, and so a different pixel format. For a given
unique subsampling, there are usually also several equivalent formats
that consist of trivial channel order rearrangements or repackings, due either to
convenience once-upon-a-time on some particular piece of hardware, or
sometimes just good old-fashioned spite.

Pixels formats are described by a unique name or fourcc code. There
are quite a few of these and there's no sense going over each one now.
Google is your friend. Be aware that fourcc codes for raw video
specify the pixel arrangement and chroma subsampling, but generally
don't imply anything certain about chroma siting or color space. YV12
video to pick one, can use JPEG, MPEG-2 or DV chroma siting, and any
one of several YUV colorspace definitions.

done!

That wraps up our not-so-quick and yet very incomplete tour of raw
video. The good news is we can already get quite a lot of real work
done using that overview. In plenty of situations, a frame of video
data is a frame of video data. The details matter, greatly, when it
come time to write software, but for now I am satisfied that the
esteemed viewer is broadly aware of the relevant issues.

Going deeper…

YCbCr is defined in terms of RGB by the ITU in two incompatible standards: Rec. 601 and Rec. 709. Both conversion standards are lossy, which has prompted some to adopt a lossless alternative called YCoCg.

Learn about high dynamic range imaging, which achieves better representation of the full range of brightnesses in the real world by using more than 8 bits per channel.

Compare with the Lab color space, mathematically equivalent but structured to account for "perceptual uniformity".

If we were all dichromats then video would only need two color channels. Some humans might be tetrachromats, in which case they would need an additional color channel for video to fully represent their vision.

Containers

So. We have audio data. We have video data. What remains is the more
familiar non-signal data and straight-up engineering that software
developers are used to, and plenty of it.

Chunks of raw audio and video data have no externally-visible
structure, but they're often uniformly sized. We could just string
them together in a rigid predetermined ordering for streaming and
storage, and some simple systems do approximately that. Compressed
frames, though, aren't necessarily a predictable size, and we usually want
some flexibility in using a range of different data types in streams.
If we string random formless data together, we lose the boundaries
that separate frames and don't necessarily know what data belongs to
which streams. A stream needs some generalized structure to be
generally useful.

In addition to our signal data, we also have our PCM and video
parameters. There's probably plenty of other metadata we also want to
deal with, like audio tags and video chapters and subtitles, all
essential components of rich media. It makes sense to place this
metadata—that is, data about the data—within the media itself.

Storing and structuring formless data and disparate metadata is the
job of a container. Containers provide framing for the data blobs,
interleave and identify multiple data streams, provide timing
information, and store the metadata necessary to parse, navigate,
manipulate, and present the media. In general, any container can hold
any kind of data. And data can be put into any container.

Going deeper…

There are several common general-purpose container formats: AVI, Matroska, Ogg, QuickTime, and many others. These can contain and interleave many different types of media streams.

Some special-purpose containers have been designed that can only hold one format:

The y4m format is the most common single-purpose container for raw YUV video. It can also be stored in a general-purpose container, for example in Ogg using OggYUV.

WAV and AIFC are semi-single-purpose formats. They're audio-only, and typically contain raw PCM audio, but are occasionally used to store other kinds of audio data ... even MP3!

Credits

In the past thirty minutes, we've covered digital audio, video, some
history, some math and a little engineering. We've barely scratched the
surface, but it's time for a well-earned break.

There's so much more to talk about, so I hope you'll join me again in
our next episode. Until then—Cheers!

Written by:
Christopher (Monty) Montgomery
and the Xiph.Org Community

Intro, title and credits music:
"Boo Boo Coming", by Joel Forrester
Performed by the Microscopic Septet
Used by permission of Cuneiform Records.
Original source track All Rights Reserved.www.cuneiformrecords.com